Abstract
With decreasing costs in robotic platforms, mobile robots that provide assistance to humans are becoming a reality. A key requirement for these types of robots is the ability to efficiently and safely navigate in populated environments. This work proposes to address this issue by studying how robots can select and follow human leaders, to take advantage of their motion in complex situations. To accomplish this, a machine learning framework is proposed, comprising data acquisition with a real robot, data labeling, feature extraction and the training of a leader classifier. Preliminary experiments combined the classification system with a multi-mode navigation algorithm, to validate this approach using an autonomous wheelchair.
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Procópio Stein is funded by INRIA’s Large-scale initiative action PAL (Personally Assisted Living) pal.inria.fr.
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References
Fulgenzi, C., Tay, C., Spalanzani, A., Laugier, C.: Probabilistic navigation in dynamic environment using rapidly-exploring random trees and gaussian processes. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sept 2008, pp. 1056–1062
Bennewitz, M., Burgard, W., Cielniak, G., Thrun, S.: Learning motion patterns of people for compliant robot motion. Int. J. Robot. Res. 24(1), 31 (2005)
Rios-Martinez, J., Spalanzani, A., Laugier, C.: Understanding human interaction for probabilistic autonomous navigation using Risk-RRT approach. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sept 2011, pp. 2014–2019
Trautman, P., Krause, A.: Unfreezing the robot: navigation in dense, interacting crowds. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2010, pp. 797–803
Mombaur, K., Truong, A., Laumond, J.: From human to humanoid locomotion—an inverse optimal control approach. Auton. Robots 28, 369–383 (2009)
Dyer, J.R., Johansson, A., Helbing, D., Couzin, I.D., Krause, J.: Leadership, consensus decision making and collective behaviour in humans. Philos. Trans. R. Soc. B: Biol. Sci. 364, 781–789 (2009)
Althoff, D., Wollherr, D., Buss, M.: Safety assessment of trajectories for navigation in uncertain and dynamic environments. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), May 2011, pp. 5407–5412
Henry, P., Vollmer, C., Ferris, B., Fox, D.: Learning to navigate through crowded environments. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), May 2010, pp. 981–986
Stein, P., Santos, V., Spalanzani, A., Laugier, C.: Navigating in populated environments by following a leader. In: International Symposium on Robot and Human Interactive Communication (RO-MAN) (2013)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3 (2009)
Almeida, J.: Target tracking using laser range finder with occlusion. Master’s thesis, Universidade de Aveiro, Aveiro, Portugal (2010)
Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 55(1), 119–139 (1997)
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© 2016 Springer International Publishing Switzerland
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Stein, P., Spalanzani, A., Santos, V., Laugier, C. (2016). Experiments in Leader Classification and Following with an Autonomous Wheelchair. In: Hsieh, M., Khatib, O., Kumar, V. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 109. Springer, Cham. https://doi.org/10.1007/978-3-319-23778-7_17
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DOI: https://doi.org/10.1007/978-3-319-23778-7_17
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